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[D] ANN – how to deal with features that can be identical from observation to observation?

Firstly to explain the situation I have to deal with in more depth:

I have a dataset for which part of the features (columns of data) are identical from observation to observation (rows) and another part of the features are variable. Roughly every 1-200 observations have some features that fall into the pattern described, whereas the dataset is very large.

Firstly, are there any specific reason why a neural network with above data would fail? Any papers/information/ideas that describe how to deal with this kind of situation?

Thanks

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.